scholarly journals Professor Gender, Age, and “Hotness” in Influencing College Students’ Generation and Interpretation of Professor Ratings

2016 ◽  
Vol 6 (3) ◽  
Author(s):  
Sara L. Sohr-Preston ◽  
Stefanie S. Boswell ◽  
Kayla McCaleb ◽  
Deanna Robertson
Keyword(s):  
College Students ◽  
Multivariate Analysis ◽  
Current Psychology ◽  
Principal Components ◽  
Psychology Students ◽  
Analysis Of Covariance ◽  
Online Ratings ◽  
Online Rating ◽  
Components Analysis ◽  
Undergraduate Psychology

<p>Undergraduate psychology students rated expectations of a bogus professor (randomly designated a man or woman and hot versus not hot) based on an online rating and sample comments as found on RateMyProfessors.com (RMP). Five professor qualities were derived using principal components analysis (PCA): dedication, attractiveness, enhancement, fairness, and clarity. Participants rated current psychology professors on the same qualities. Current professors were divided based on gender (man or woman), age (under 35 or 35 and older), and attractiveness (at or below the median or above the median). Using multivariate analysis of covariance (MANCOVA), students expected hot professors to be more attractive but lower in clarity. They rated current professors as lowest in clarity when a man and 35 or older. Current professors were rated significantly lower in dedication, enhancement, fairness, and clarity when rated at or below the median on attractiveness. Results, with previous research, suggest numerous factors, largely out of professors’ control, influencing how students interpret and create professor ratings. Caution is therefore warranted in using online ratings to select courses or make hiring and promotion decisions. </p>

Morphological variation in relation to the taxonomy of the destructor group of the genus Cherax

1988 ◽  
Vol 2 (1) ◽  
pp. 55 ◽  
Author(s):  
A Sokol
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Morphological Variation ◽  
Analysis Of Covariance ◽  
Bivariate Analysis ◽  
Morphological Divergence ◽  
Analysis Techniques ◽  
Late Tertiary ◽  
Outgroup Species ◽  
Components Analysis

The present study was directed at clarifying the taxonomy of the destructor group of the genus Cherax. This group was defined by Riek (1969) to include four species: C. destructor Clark, C. albidus Clark, C. davisi Clark and C. esculus Riek. Approximately 1600 specimens representing over 80 localities were examined, including specimens from three outgroup species; C. rotundus, C. punctatus and C. dispar. Variation in 16 metric and 30 multistate characters was analysed by bivariate (analysis of covariance) and multivariate (principal components analysis) techniques. None of the taxonomic analyses supported the distinction of C. davisi or C. esculus from C. destructor, which suggests that the two former species be synonymised with the last. By contrast, C. albidus was found to be morphologically distinct. The pattern and timing of speciation of C. albidus and C. destructor are unclear but may relate to the increase in aridity in inland Australia during the late Tertiary. The analyses also indicated that heterochrony may underly the morphological divergence of these two species.

Period-Luminosity-Shape of Light Curve Relation for Cepheids in LMC and SMC

2005 ◽  
Vol 201 ◽  
pp. 480-481
Author(s):  
P. Ligeza ◽  
P. Moskalik ◽  
A. Schwarzenberg-Czerny
Keyword(s):  
Light Curve ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Fundamental Mode ◽  
Light Curves ◽  
Analysis Of Covariance ◽  
Curve Shape ◽  
Long Period ◽  
Classical Cepheids ◽  
Components Analysis

In this paper we report our analysis of the period-luminosity-shape of light curve (P-L-S) relation. The data we used came from LMC and SMC Cepheid light curves produced by OGLE-II microlensing survey. We used Principal Components Analysis of covariance matrix of the sets for Cepheids in LMC and SMC separately. Our calibrating set was bounded to long period classical Cepheids pulsating in fundamental mode. The results are used to derive a method for estimation of distances from light curve shape.

Big-Five Adjective Marker Scales for Use with College Students

1995 ◽  
Vol 77 (1) ◽  
pp. 160-162 ◽  
Author(s):  
Ralph L. Piedmont
Keyword(s):  
College Students ◽  
Principal Components Analysis ◽  
Big Five ◽  
Principal Components ◽  
Factor Model ◽  
Five Factor Model ◽  
Procrustes Rotation ◽  
College Sample ◽  
Five Factors ◽  
Components Analysis

This report evaluated the psychometric integrity of an 80-item bipolar adjective scale which assesses the dimensions of the five-factor model of personality. Using a college sample of 149 women and 30 men, a principal components analysis employing an orthogonal Procrustes rotation identified the five factors which were comparable to factor structures found with adults. Researchers can therefore have some confidence in using these marker scales with college students.

scholarly journals Using ePortfolio-based Learning Approach to Facilitate Knowledge Sharing and Creation of College Students

2017 ◽  
Author(s):  
Chi-Cheng Chang ◽  
Pao-Nan Chou ◽  
Chaoyan Liang
Keyword(s):  
College Students ◽  
Multivariate Analysis ◽  
Knowledge Sharing ◽  
T Test ◽  
Analysis Of Covariance ◽  
Control Group ◽  
Learning Approach ◽  
Before And After ◽  
Group A ◽  
Experimental Group

The purpose of the present study was to examine the effects of the ePortfolio-based learning approach (ePBLA) on knowledge sharing and creation with 92 college students majoring in electrical engineering as the participants. Multivariate analysis of covariance (MANCOVA) with a covariance of pretest on knowledge sharing and creation was conducted for examining differences in knowledge sharing and creation between an experimental group (a total of 47 participants using ePBLA) and a control group (a total of 45 participants not using ePBLA or creating eportfolio). A t-test was also performed for examining the differences in knowledge sharing and creation of the experimental group before and after using ePBLA. The results showed that: a) the experimental group had significantly better knowledge sharing and creation than the control group; and b) the experimental group had significantly better knowledge sharing and creation after using ePBLA. The results implied that ePBLA facilitated knowledge sharing and creation. Furthermore, relationships between knowledge sharing and creation were also enhanced by the use of ePBLA

Sensory Lexicon for Fresh Squeezed and Processed Orange Juices

2008 ◽  
Vol 14 (5_suppl) ◽  
pp. 131-141 ◽  
Author(s):  
P. Ruiz Pérez-Cacho ◽  
H. Galan-Soldevilla ◽  
K. Mahattanatawee ◽  
A. Elston ◽  
R.L. Rouseff
Keyword(s):  
Multivariate Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Processing Technology ◽  
Sensory Panel ◽  
Geometric Means ◽  
Thermally Processed ◽  
Components Analysis ◽  
Tactile Sensations

The aim of this study was to develop a flavor vocabulary (odor, aroma basic tastes and trigeminal/tactile sensations) to describe both fresh-squeezed and thermally processed (commercial) orange juices. Two independent panels located in different countries (Spain and USA) selected a common lexicon using multivariate analysis. Two sets of samples were selected and evaluated independently: the American sensory panel analyzed 40 orange juices varied in processing technology (pasteurized, refrigerated from concentrated, frozen concentrated and canned juices) and cultivars (Valencia, Temple, Navel, Hamlin, and Amber Sweet). The Spanish panel analyzed 26 samples that included thermally processed juices (pasteurized and refrigerated from concentrated) and unheated, hand squeezed juices (Valencia and Navel). A total of 34 common attributes were selected (15 for odor, 12 for aroma, 3 for basic tastes and 4 for trigeminal/tactile sensations). Data obtained were analyzed by geometric means, principal components analysis (PCA) and by Kruskal-Wallis test. Significant differences between the major categories of commercial juices were observed for all attributes in both countries and were also observed between fresh-squeezed and processed orange juices.

Allport-Vernon-Lindzey Study of Values: 1. Factor Structure for a Combined Sample of Male and Female College Students

1970 ◽  
Vol 27 (3) ◽  
pp. 955-958 ◽  
Author(s):  
Rio Sciortino
Keyword(s):  
College Students ◽  
Principal Components Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
The Self ◽  
Female College Students ◽  
Male And Female ◽  
Female College ◽  
Components Analysis

A principal components analysis was performed on the self-ratings (for a combined sample) obtained from the Allport-Vernon-Lindzey Study of Values ( N = 150 combined sample of 102 male and 48 female college students). The obtained principal components were then rotated according to the varimax procedure. The varimax factors obtained were: esthetic, social, and religious.

A multivariate analysis of the niches of plant populations in raised bogs. II. Niche width and overlap

1977 ◽  
Vol 55 (9) ◽  
pp. 1211-1220 ◽  
Author(s):  
E. A. Johnson
Keyword(s):  
Multivariate Analysis ◽  
Species Richness ◽  
Principal Components ◽  
Niche Differentiation ◽  
Niche Width ◽  
Ecological Niches ◽  
Environmental Complexity ◽  
Plant Populations ◽  
Raised Bogs ◽  
Components Analysis

The results of a principal components analysis are used to define the ecological niches of the plant populations in raised bogs. This paper examines the niche parameters of width and overlap. Dominance is positively related to niche width and inversely related to the number of species (richness). Richness is shown to be positively related to increased environmental complexity and predictability. Dominants appear to decrease in environments that are more complex and predictable because as a class these organisms are less opportunistic. Niche differentiation measured as overlap is greater in the richer, more environmentally complex and predictable parts of raised bogs.

scholarly journals Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks

The Analyst ◽  
2016 ◽  
Vol 141 (1) ◽  
pp. 90-95 ◽  
Author(s):  
S. Van Nuffel ◽  
C. Parmenter ◽  
D. J. Scurr ◽  
N. A. Russell ◽  
M. Zelzer
Keyword(s):  
Multivariate Analysis ◽  
Principal Components Analysis ◽  
Method Validation ◽  
Cell Cultures ◽  
Principal Components ◽  
Neuronal Cell ◽  
Training Set ◽  
Neuronal Cell Cultures ◽  
Tof Sims ◽  
Components Analysis

Here, we demonstrate that by using a training set approach principal components analysis (PCA) can be performed on large 3D ToF-SIMS images of neuronal cell cultures.

Robust Statistics: A Survey and Some Prescriptions

1976 ◽  
Vol 1 (4) ◽  
pp. 285-312 ◽  
Author(s):  
Howard Wainer
Keyword(s):  
Factor Analysis ◽  
Multivariate Analysis ◽  
Standard Deviation ◽  
Principal Components Analysis ◽  
Analysis Of Variance ◽  
Principal Components ◽  
Robust Statistics ◽  
Robust Methods ◽  
The Mean ◽  
Components Analysis

It is noted that the usual estimators that are optimal under a Gaussian assumption are very vulnerable to the effects of outliers. A survey of robust alternatives to the mean, standard deviation, product moment correlation, t-test, and analysis of variance is offered. Robust methods of factor analysis, principal components analysis and multivariate analysis of variance are also surveyed, as are schemes for outlier detection.

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